Structure-property Relationships Research Articles

Pressure-induced abnormal blue-shift emission enhancement and phase transition of perovskite DMAPbI3

Designing low-dimensional hybrid organic–inorganic perovskites (HOIPs) with enhanced broadband emission under ambient conditions remains a pressing challenge. Here, interesting results of emission blueshift and enhancement were successfully achieved by pressure modulation of the (NH2(CH3)2PbI3 ((NH2(CH3)2 = DMA) structure. The observed rapid blueshifted emission is closely related to the distortion of PbI6 octahedron induced by phase transition from the P63/mc phase to the P1 phase at 0.8 GPa, which has been confirmed by in situ high-pressure PL, UV–vis absorption, synchrotron XRD and Raman spectroscopy. The pressure-induced PL enhancement of DMAPbI3 can be ascribed to the mechanism that the distorted PbI6 octahedrons promote the radiative recombination of self-trapped excitons by increasing the activation barrier energy for detrapping. The PL intensity enhancement was retained at 4 times the initial value after the pressure was released. These findings deepen the understanding of the structure-property relationships of one-dimensional perovskite and reveal the roles of pressure in regulating the optical properties of perovskites.

Prediction of CO2 solubility in aqueous amine solutions using machine learning method

In this study, a quantitative structure–property relationship (QSPR) model has been designed based on machine learning (ML) to offer a new method to accurately predict carbon dioxide (CO2) solubility in aqueous amine solutions. Molecular descriptors are used to denote representative features of the amine molecular structure supplemented with amine solution concentration, CO2 partial pressure, and temperature as inputs to the model. The coefficient of determination (R2) of the well-trained ML model reaches 0.971, and the average absolute deviation (AAD) of independent experimental validation is 4.785 %, effectively demonstrating the model’s reliability and generalization performance. Finally, SHapley Additive exPlanations (SHAP) is adopted to reveal the contribution of different features to the model predictions, making the model more transparent and interpretable. Overall work provides a novel, low-cost, efficient method to predict equilibrium CO2 solubility in aqueous amine solution and offers a new perspective in developing advanced amine for CO2 capture.

Structure-property relationship of a complex photoluminescent arylacetylide-gold(I) compound. I: a pressure-induced phase transformation caught in the act.

A pressure-induced triclinic-to-monoclinic phase transition has been caught `in the act' over a wider series of high-pressure synchrotron diffraction experiments conducted on a large, photoluminescent organo-gold(I) compound. Here, we describe the mechanism of this single-crystal-to-single-crystal phase transition, the onset of which occurs at ∼0.6 GPa, and we report a high-quality structure of the new monoclinic phase, refined using aspherical atomic scattering factors. Our case illustrates how conducting a fast series of diffraction experiments, enabled by modern equipment at synchrotron facilities, can lead to overestimation of the actual pressure of a phase transition due to slow transformation kinetics.

Predicting bioconcentration factors (BCFs) for per- and polyfluoroalkyl substances (PFAS)

The bioconcentration factor (BCF) is an important parameter that gives information regarding the ability of a contaminant to be taken up by organisms from the water. Per- and polyfluoroalkyl substances (PFAS) are widespread in the environment, causing concern regarding their impact on human health. Due to the lack of available bioaccumulation data for most compounds in the PFAS group, we developed a quantitative structure-property relationship (QSPR) model to predict the log BCF for fish (taxonomic class Teleostei), based on experimental data available for the most studied 33 representatives of this group of compounds. Furthermore, we implemented the developed model to predict log BCF for an external dataset of 2209 PFAS. Consequently, 1045 PFAS were found not to be bioaccumulative, 208 were classified as bioaccumulative, and 956 were predicted to be very bioaccumulative. Finally, we obtained the high correlation (R2 = 0.844) between the log BCFs obtained in laboratory and field studies for 13 PFAS. In silico analyses indicate that PFAS bioconcentration depends on the size (chain length – number of CF2 groups in alkyl tail/chain) of a molecule, as well as on the atomic distribution properties. In general, long-chain PFAS - above 8 and 6 carbon atoms for perfluorinated carboxylic acids (PFCAs)and perfluorinated sulfonic acids (PFSAs), respectively - tend to bioconcentrate more compared to the short-chain ones. In conclusion, predicting BCF on fish is possible for a wide range of fluorinated compounds, which can be further used for estimating PFAS behavior in the environment.

Prediction of the heats of combustion for food-related organic compounds. A quantitative structure–property relationship (QSPR) study

Prediction of the heats of combustion for food-related organic compounds. A quantitative structure–property relationship (QSPR) study

Effects of spatial microstructure characteristics on mechanical properties of dual phase steel by inverse analysis and machine learning approach

This work aims to investigate complex relationship between microstructure characteristics and mechanical properties of dual phase (DP) steel through an inverse analysis based on Markov chain Monte Carlo (MCMC) method combined with meso-scale material modelling. In this framework, a machine learning approach as surrogate model was developed, in which support vector regression (SVR) and artificial neural network (ANN) were trained using results from representative volume element (RVE) simulations coupled with damage model, which were previously calibrated with experimental data of commercial DP steel grades. Moreover, specific microstructure descriptors including Moran’s index, martensite band index and martensite orientation were proposed for representing effects of spatial distributions of martensitic phase. As a result, inverse predictions of microstructure characteristics of DP steels for achieving defined yield strength, tensile strength, uniform elongation and toughness were presented. The inverse analysis could solve the non-uniqueness of structure–property relationships of steel, whereby significances of dispersed structures and aligned martensite bands were highlighted in details. The approach fairly dealt with multi-target optimization and high dimensional problem, which can be further applied as a guideline for designing DP microstructures with enhanced mechanical properties.

Morphology and Emulsification of Poly(N-2-(methacryloyloxy) ethyl pyrrolidone)-b-poly(benzyl methacrylate) Assemblies by Polymerization-Induced Self-Assembly.

In this work, a series of amphiphilic diblock copolymers poly(N-2-(methacryloyloxy) ethyl pyrrolidone)-b-poly(benzyl methacrylate) (PNMP m -b-PBzMA n ) were developed by the dispersion polymerization method in ethanol. The polymerization-induced self-assembly (PISA) behaviors were studied systematically, and a comprehensive structure-property relationship was also established. Two distinct PISA tendencies were observed, which was mainly depended on the polymerization degree m of PNMP segment. When m is small such as 39 and 55, morphological transitions from spherical to vesicle-like assemblies via wormlike ones upon increasing n commonly happen regardless of the solid content. Alternatively, spherical assemblies became the sole morphology for PNMP64-b-PBzMA n block copolymers because of the excellent solvophilicity of the PNMP64 segment. Attributing to the amphiphilicity of PNMP m -b-PBzMA n block copolymers, PNMP m -b-PBzMA n assemblies by PISA are a type of excellent Pickering emulsifiers. These assemblies prefer to stabilize O/W Pickering emulsions as confirmed by the confocal laser scanning microscopy method, and the effects of polymerization degree of PBzMA segment or morphologies of PNMP m -b-PBzMA n assemblies are finite.

Pharmacophore Identification and Structure-Activity Relationship Analysis of a Series of Substituted Azaindoles as Inhibitors of Trypanosoma brucei.

Human African trypanosomiasis is among the World Health Organization's designated neglected tropical diseases. Repurposing strategies are often employed in academic drug discovery programs due to financial limitations, and in this instance, we used human kinase inhibitor chemotypes to identify substituted 4-aminoazaindoles, exemplified by 1. Structure-activity and structure-property relationship analysis, informed by cheminformatics, identified 4s as a potent inhibitor of Trypanosoma brucei growth. While 4s appeared to be fast acting and cidal in the in vitro assays, it failed to cure a murine model of infection. Preliminary efforts to identify the potential mechanism of action of the series pointed to arginine kinase, though, as we demonstrate, this does not appear to be the sole target of our compounds. This comprehensive approach to drug discovery, encompassing cheminformatics, structure-potency and structure-property analysis, and pharmacophore identification, highlights our multipronged efforts to identify novel lead compounds for this deadly disease.

Data-driven integration of synthetic representative volume elements and machine learning for improved microstructure-property linkage and material performance in ceramics

Ceramic materials, characterized by their heat resistance, dielectric properties, and mechanical performance, are often compromised by brittleness due to microstructural inclusions. These inclusions, such as defects, secondary phases, and pores, are critically analyzed for their impact on material strength and fracture properties. In this study, the linkage between microstructure and properties in ceramic materials is explored through a methodological approach that combines experimental observations with physics-based and machine learning models. A data-driven approach has been employed, utilizing synthetic Representative Volume Elements (RVEs) derived from X-ray computed tomography scans of ceramics. The methodology involves an automated finite element (FE) simulation process for progressive failure analysis under uniaxial compression and tension. The analysis is conducted using statistical, data-driven, and machine learning techniques, including principal component analysis and k-means clustering, to assess the microstructural features' impact on material performance. The study focuses on the use of RVEs for accurately capturing essential microstructural characteristics and addresses the challenges in developing synthetic models and the limitations of simulation capabilities. The study's findings reveal that less uniform inclusion distribution and a higher standard deviation in inclusion size correlate to lower mechanical performance. By applying data-driven methods, this research contributes to the optimization of material performance and the establishment of structure-property relationships, with a particular emphasis on the influence of inclusions and defects on the mechanical behavior of ceramic materials.

3D MXene architectures for electromagnetic protection

Electromagnetic (EM) pollution is becoming increasingly severe due to the explosive growth of various communication devices. EM protection materials are the key to solving EM pollution. MXenes, by virtue of larger specific surface area, numerous surface functional groups and excellent conductivity, are attracting increasing attention and showing competitive performance in EM protection. By constructing 3D MXene architectures, not only can the EM protection performance be significantly improved, but it can also meet the development needs of lightweight, miniaturization, and portability in the future. In this review, we summarized the methods for preparing 3D MXene architectures applied in the field of EM protection. Then, we comprehensively elaborate on the structure-property relationships of 3D MXene architectures and their applications in microwave absorption (MA) and electromagnetic interference (EMI) shielding. Finally, we discuss the challenges and opportunities in the development of 3D MXene architectures for EM protection.

Controllable Preparation of a Cu NCs@Zn-MOF Hybrid with Dual Emission Induced by an Ion Exchange Strategy for the Detection of Explosives.

The precise synthesis of Cu NCs is a highly desirable and controllable route for the preparation of desired structures and properties, which facilitates the rational design of valuable probes for fluorescence sensing and the understanding of structure-property relationships. Herein, an ion-exchange strategy combined with a bottom-up synthetic approach was utilized in the synthesis process of Cu NCs for the first time, which achieved the controllable synthesis of Cu NCs and in situ anchoring of Cu NCs on the support material HPU-14. The as-prepared Cu NCs@HPU-14-4h not only had a good peroxidase-like property but also exhibited stable dual-emitting fluorescence at 470 and 620 nm. Notably, the peroxidase-like property endowed Cu NCs@HPU-14-4h with the capability of highly sensitive colorimetric detection of H2O2 in a linear concentration from 0.1 to 140 μM (detection limit of 86.7 nM), and a change in the fluorescent color from red to blue could be observed by the naked eye. Furthermore, due to the large overlap between the absorption of 2,4,6-trinitrophenol (TNP) and the excitation band of Cu NCs@HPU-14-4h, TNP could also be detected from 27 types of analogs and common ions with a limit of detection of 68 nM. Finally, a portable hydrogel probe with efficient wipe sampling was fabricated by polyvinyl alcohol (PVA) comprising Cu NCs@HPU-14-4h with the aim of on-site visualization of different explosives. Consequently, the current study not only provides a new idea for the precise synthesis of Cu NCs and their controllable anchoring on support materials but also offers an effective method for predicting H2O2 and TNP.

Strain phase equilibria and phase‐field method of ferroelectric polydomain: A case study of monoclinic KxNa1 − xNbO3 thin films

AbstractKnowledge of the thermodynamic equilibria and domain structures of ferroelectrics is critical to establishing their structure–property relationships that underpin their applications from piezoelectric devices to nonlinear optics. Here, we establish the strain condition for strain phase separation and polydomain formation and analytically predict the corresponding domain volume fractions and wall orientations of, relatively low symmetry and theoretically more challenging, monoclinic ferroelectric thin films by integrating thermodynamics of ferroelectrics, strain phase equilibria theory, microelasticity, and phase‐field method. Using monoclinic KxNa1 − xNbO3(0.5 < x < 1.0) thin films as a model system, we establish the polydomain strain–strain phase diagrams, from which we identify two types of monoclinic polydomain structures. The analytically predicted strain conditions of formation, domain volume fractions, and domain wall orientations for the two polydomain structures are consistent with phase‐field simulations and in good agreement with experimental results in the literature. The present study demonstrates a general, powerful analytical theoretical framework to predict the strain phase equilibria and domain wall orientations of polydomain structures applicable to both high‐ and low‐symmetry ferroelectrics and provide fundamental insights into the equilibrium domain structures of ferroelectric KxNa1 − xNbO3 thin films that are of technology relevance for lead‐free dielectric and piezoelectric applications.

Vaporisation Thermodynamics: Are Triazolium Ionic Liquids a Real Alternative to Popular Imidazolium-Based Ionic Liquids?

New experimental vapour pressures and vaporisation enthalpies of the ionic liquids [2,4-dimethyl-1,2,4-triazolium][NTf2], [2-methyl-4-ethyl-1,2,4-triazolium][NTf2], and [2-ethyl-4-methyl-1,2,4-triazolium][NTf2] were measured using the Langmuir method in combination with the quartz crystal microbalance. New experimental vapour pressures and vaporisation enthalpies of the molecular liquids 1H-1,2,4-triazole, 1-methyl-1,2,4-triazole, 1-ethyl-1,2,4-triazole, and 1H-1,2,3-triazole were measured using the transpiration method. Structure–property relationships between molecular and ionic liquids were studied. These results will facilitate chemical engineering calculations of processes involving ILs.

Statistical Evaluation of Cancer Drugs by QSPR Modeling

The prospect of discovering a cure for cancer has been present for the past two to three decades. Annually, this illness affects approximately 10 million individuals worldwide. Anticancer medications are pivotal in treating cancer and other malignant diseases. In this paper, the physical properties and chemical reactions associated with the anticancer medications of various topological indices (TIs) have been established. Additionally, we have discussed the degree-based TIs and their Quantitative Structure-Property Relationship (QSPR) analysis. In mathematical chemistry, molecular descriptors are essential, particularly for researchers investigating Quantitative Structure-Activity Relationship (QSAR) and QSPR models. The goal of the QSPR study is to establish a mathematical relationship between the properties under investigation (such as boiling point and flash point) and various descriptors related to the molecular structure of the drugs. Furthermore, we show the correlation with the physicochemical properties of anticancer medications.

Controlling Mechanical Properties of Medical-Grade Scaffolds through Electrospinning Parameter Selection.

Electrospinning (ES) is a versatile process mode for creating fibrous materials with various structures that have broad applications ranging from regenerative medicine to tissue engineering and surgical mesh implants. The recent commercialization of this technology for implant use has driven the use of resorbable electrospun products. Resorbable electrospun meshes offer great promise as temporary implants that can utilize the layer upon layer method of additive manufacturing to incorporate porosity as a function of process parameters into a scaffold structure. The interconnected porosity and feature size known to ES have previously been observed to hold great potential for simulating the natural cellular environment of soft tissue. This microstructure, proper degradation kinetics, and mechanical properties combine to provide the design basis for artificial tissue structures that could aid in not only wound healing but also true tissue engineering and regenerative medicine. While current advancement in the field is understood to be limited by material properties, the importance of optimizing mechanical properties with currently available materials should not be overlooked. This work investigated the process parameter effects and interactions that control the structure-property relationship for a range of medical-grade aliphatic polyester materials with a range of intrinsic properties. An ε-caprolactone homopolymer (PCL), l-lactide homopolymer (PLLA), and Lactoflex, a copolymer with intermediate properties relative to the homopolymers, were characterized before, during, and after the additive manufacturing process. The interacting effects of process parameters, distance to collector, and dispensing rate were shown to produce variable-density, nonwoven scaffold structures. The resorbable mesh scaffolds of PLLA, PCL, and Lactoflex demonstrated a broad range of mechanical properties (approximately 1-10 MPa ultimate tensile strength and 5-390 MPa tensile modulus). Postprocessing of scaffolds demonstrated removal of solvents and preservation of micrometer-sized features. Resorbable polymers and electrospinning can produce scaffold materials with excellent features and offer tremendous potential in the field of implantable resorbable devices.

Factor Analysis-Based Selection of Xanthoceras Sorbifolia Bunge Oil as a Promising Bio-Based Lubricant

Abstract With increasing environmental awareness, the demand for bio-based lubricants is escalating, positioning vegetable oils as viable alternatives to traditional industrial lubricants. This study is based on the previously established quantitative structure-property relationship - multiple linear regression (QSPR-MLR) model. Then, it employs comprehensive factor scores to assess and rank the anti-wear properties and oxidation stability of 53 vegetable oils with diverse fatty acid compositions. Xanthoceras sorbifolia Bunge oil (XSBO), derived from woody oil plants renowned for their economic and environmental benefits, emerges as a standout candidate following exclusion of previously reported lubricant types. Comparative evaluations via four-ball friction tests and pressurized differential scanning calorimeter (PDSC) analyses reveal XSBO's antioxidant properties are slightly inferior to mineral oils, poly-a-olefins, and synthetic esters. However, XSBO exhibits superior tribological properties and viscosity characteristics. Supported by computational modeling and laboratory validation, XSBO demonstrates significant promise as a bio-based lubricant, advocating its potential as an ideal replacement for conventional base oils.

Structure-property relationship between different molecular precursors and the final properties of carbon dots: Preparation, characterization and applications as sensors for metal ions

Carbon dots (CDs) have attracted significant attention in recent years due to their interesting properties, such as photoluminescence, biocompatibility, excellent water dispersibility, as well as their potential applications in different fields. Despite these features, the complexity of their photoluminescent properties remains a subject of ongoing research and still presents unresolved questions. In this work, we investigated the preparation of various CDs from different low molecular mass starting materials containing carbon, nitrogen and/or sulfur, using hydrothermal carbonization as the preparation method. The CDs were characterized using various techniques, including TEM, FTIR, photoluminescence, UV–Vis, Raman and XPS. A detailed analysis of the initial reactions between the precursors was conducted, and our main results suggest that the optical properties of the CDs are related to fluorophores formed during the initial Michael condensation reactions between the precursors. This process produces molecular fluorescence, which plays a pivotal role in the photoluminescence properties of the nanoparticles. In addition, two of the obtained CDs were used as selective and sensitive probes for metal ions, achieving a detection limit of 0.58 μM and 0.55 μM. Finally, the findings described here can guide future works in fine-tuning the design of CDs with desired properties and different potential applications.

Structure-property relations in rheology of cellulose nanofibrils-based hydrogels

Hydrogels prepared from self-assembled cellulose nanofibrils (CNFs) are widely used in biomedicine, electronics and environmental technology. Their ability to serve as inks for extrusion-based 3D printing is conventionally evaluated by means of rheological tests. A model is developed that describes the response of CNF gels in small- and large-amplitude oscillatory tests in a unified manner. The model involves a reasonably small number of material parameters, ensures good agreement between results of simulation and observations in oscillatory tests and correctly predicts the stress–strain Lissajous curves, experimental data in hysteresis loop tests, and measurements of the steady-state viscosity. The model is applied to analyze how composition and preparation conditions for CNF gels affect transition from shear thinning to weak strain overshoot in large-amplitude shear oscillatory tests. Based on the model, simple relations are derived for the fractal dimension of CNF clusters and the storage modulus of gels prepared in aqueous solutions of multivalent salts. The validity of these equations is confirmed by comparison of their predictions with observations in independent tests.

Novel singlet fission chromophores: Boron/nitrogen para-substituted acenes

Singlet fission (SF) process has attracted growing attention because of its potential capability to overcome the Shockley−Queisser limit on solar cells. So the raising of new molecule with SF character is crucial for its widespread application. In this work, the structure-property relationships of series of boron and nitrogen para-substituted (para-BN-BN and para-BN-NB) anthracene (A-n and A′-n), tetracene (T-n and T′-n), pentacene (P-n and P′-n) and hexacene (H-n and H′-n) are studied to propose novel strategy of designing SF molecule. Among these structures, the number (n) of central rings between para-(BN)2-substituted six-membered rings can efficiently adjust the area of aromaticity, the diradical characters, which provide the low-lying T1-state energy and further favoring the availability of efficient SF molecules. We hope present work can provide novel design strategies toward the discovery of bright SF chromophores for the application to efficient organic solar cells.

Modular design of Diels-Alder reversible networks for the facile production of highly tunable materials

Covalent adaptable networks (CANs) have attracted significant attention due to their potential to form crosslinked, yet reprocessable networks. Their ability to rearrange upon exposure to specific stimuli, in combination with properties such as self-healing can advance the development of novel materials, including for additive manufacturing. Thorough understanding of structure-property relations and processing potential will aid future application-driven research in network design as well as material selection. Therefore, a multitude of CANs were synthesized herein, by crosslinking epoxide-based oligomers via the furan-maleimide Diels-Alder reaction, to evaluate small systematic variations of (co)monomer composition, crosslinker length/flexibility and crosslinking density as vectors of tuning the CANs' thermomechanical properties. Networks with glass transition temperatures (Tg) spanning from <−40 °C up to >20 °C and Young's Moduli spanning from 0.2 MPa to >500 MPa were readily attainable. Crosslinker length/flexibility had a profound impact on the tensile properties, while changes in backbone composition provided insight into the impact of secondary interactions versus rigid moieties on mechanical performance. Self-healing at ambient conditions was demonstrated for elastomeric networks, with healing efficiency being enhanced when using longer crosslinkers. Finally, a cell viability and metabolic activity assay provided a preliminary in vitro demonstration of the biocompatibility of these materials.